CN105578388A - Maritime search and rescue wireless sensing network system and robustness route method thereof - Google Patents

Abstract

The invention discloses a maritime search and rescue wireless sensing network system. The maritime search and rescue wireless sensing network system comprises a plurality of wireless sensing network nodes, a plurality of aggregation nodes, a plurality of search and rescue terminals and a coast station or ground control center. The plurality of wireless sensing network nodes are distributed on the sea at random and construct a wireless sensing network in a self-organizing mode, and each wireless sensing network node is used for collecting search and rescue information data. The aggregation nodes and the wireless sensing network nodes carry out information interaction in a wireless communication mode, and the aggregation nodes transmit the search and rescue information data collected by the wireless sensing network nodes to the search and rescue terminals. The search and rescue terminals are connected to an internet through a satellite. The coast station or ground control center carries out subsequent processing on the search and rescue information data through the internet. The invention further discloses a robustness route method of the maritime search and rescue wireless sensing network. The maritime search and rescue wireless sensing network system and the robustness route method can be applicable to the network relatively high in dynamics and unstable in link quality, and unnecessary energy consumption is reduced.

Description

A kind of maritime search and rescue wireless sensing network system and robust method for routing thereof

Technical field

The present invention relates to sensor network applied technical field, be specifically related to a kind of maritime search and rescue wireless sensing network system and robust method for routing thereof.

Background technology

Traditional maritime search and rescue system realizes the GMDSS (GMDSS) of rescue when being and occurring for casualty by International Maritime Organization, when having an accident, wrecked emergency is realized by the Rescue Radar response on ship, satellite communication system and landline networks, search and rescue receive centre is on the bank after distress signal, according to radar information in wrecked the search launching blanket type, significantly, there is the defects such as cost is high, efficiency is low in this search and rescue, and search and rescue side can not obtain the current vital sign information of persons falling in water.

Wireless sensor network (WirelessSensorNetworks, WSN) develops rapidly, the characteristic of, MANET low with little, the easy deployment of its volume, cost, be wireless communication field inject new may.Sensor node self-organizing can form a multihop network, and they can collect positional information and the vital sign information of overboard target in time, and send to search and rescue side, greatly improves the search efficiency of search and rescue side.

Wireless sense network, with the superiority of its uniqueness, can be deployed in the place that the mankind cannot relate to and complete some Detection tasks, be obtained for and apply widely in military affairs, medical treatment, household, environment etc.This year, at sea field have also been obtained application, as marine oil overflow detection, maritime environment monitoring, navigation channel detection etc., wireless sensor node builds network with the form of self-organizing, and interested for monitoring side data are transmitted by network, marine real time information can be obtained, operating efficiency is high and cost is low, known by analyzing, and wireless sense network is also applicable to being applied to maritime search and rescue very much.

Wireless sense network is distributed in sea, due to the complexity of maritime environment, a major issue that first will solve is exactly the high-quality transmission how ensureing data, the persons falling in water information namely how monitored by wireless sensor node, by stable communication link, send to land search and rescue center.

The routing issue of WSN is not because of excessive power consumption under the prerequisite of death at guarantee node, a metastable path is selected to carry out transfer of data, even if in the maritime environment of complexity, routing algorithm can adjust in time to the mobility of node, there is good autgmentability and robustness, reduce packet loss, ensure the communication quality of data.The research majority of present stage is static wireless sense network, and as forest fire protection, building monitoring, Geological Hazards Monitoring etc., in such applied environment, node location is fixed, and network topology can not change, and communication link is more stable.Therefore, can not directly existing algorithm be directly attached in marine wireless sense network.

The environmental limitations of marine wireless sense network residing for it, will face huge challenge in the design process of routing algorithm.Be mainly reflected in: the node energy in network is not inexhaustible, and be that random placement is in the maritime environment of complexity, supplementing of energy cannot be realized, and be subject to the impact of maritime environment, and the feature that node mobility is strong, cause the communication link between arbitrary node intermittent, newly-designed routing algorithm must can ensure the stability of link for this reason.

Although current algorism for routing wireless sensing network is optimized the energy ezpenditure in network, the network topology change caused for the mobility of network also has research, but deficiency is still had to the research of link stability, cannot directly by existing Mobile routing algorithm application to marine, therefore to consider in the design of routing algorithm several in:

(1) link stability.The interruption of communication link can cause the time delay increasing transfer of data, even causes the loss of packet.

(2) balancing energy.In the process of Route Selection, choose consistent link and transmit, cause the load down of link, need equilibrium assignment network task.

(3) life span of network.Wireless sense network plays a significant role at sea searching and rescuing, and the time of network survivability is longer, and guarantee searches and rescues achievement.

(4) good autgmentability.Due to the movement of node, the position of node changes often, in Cluster Networks, needs network to make response in time to mobile node.

Summary of the invention

The object of the present invention is to provide a kind of maritime search and rescue wireless sensing network system and robust method for routing thereof, solve the problem that in existing maritime search and rescue wireless sense network, data transmission quality is low, dynamic can be adapted to higher, the network of link-quality instability, and reduce unnecessary energy ezpenditure.

In order to achieve the above object, the present invention is achieved through the following technical solutions: a kind of maritime search and rescue wireless sensing network system, is characterized in, comprises:

Several wireless sensing net nodes, several aggregation nodes, several search and rescue terminals and base station or ground control centre;

Several described wireless sensing net node random distribution, and build wireless sense network by the form of self-organizing at sea, and wireless sensing net node described in each is for gathering search and rescue information data;

Described aggregation node and wireless sensing net node carry out information interaction by communication, the search and rescue information data transmission that wireless sensing net node collects by described aggregation node is to searching and rescuing terminal, described search and rescue terminal is connected to Internet by satellite, and base station or ground control centre carry out subsequent treatment by Internet to search and rescue information data.

Several described wireless sensing net nodes comprise the wireless sensing net node being arranged on wireless sensing net node on life vest or goods and search and rescue side and manually shedding; Several described aggregation nodes are arranged on lifeboat raft; Described search and rescue terminal is arranged on boats and ships or searches and rescues on aircraft; Wherein the primary power of several wireless sensing net nodes is identical.

Described search and rescue information data comprises goods information and/or vital sign information and/or geographical position.

A robust method for routing for maritime search and rescue radio sensing network, is applied to maritime search and rescue wireless sensing network system, is characterized in, comprise following steps:

S1, sub-clustering stage, adopt the cluster algorithm based on geographical position that several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out sub-clustering according to virtual grid, the wireless sensing net node being positioned at same virtual grid is same bunch, and any wireless sensing net node met in adjacent virtual grid can communicate;

S2, cluster head are elected, and several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out initialization, calculates the probability that each wireless sensing net node is elected to cluster head, and select cluster head node at random in the mode that wheel turns;

S3, Route Selection, all cluster head node in maritime search and rescue wireless sensing network system build the backbone links collection of data retransmission, cluster head node to bunch in the search and rescue information data that collects of all the other nodes carry out integration process, and forward the search and rescue information data that all the other cluster head node send;

S4, transfer of data, adopt default link stability assessment algorithm to carry out stability measurement to all data retransmission backbone links that the data retransmission backbone links that cluster head node builds is concentrated, select optimal data to forward backbone links and will integrate the search and rescue information data transmission after processing to aggregation node.

Specifically comprise in described step S2:

Each wireless sensing net node in bunch calculates oneself elected possibility according to the select probability of cluster head, and bunch in broadcast;

Receive the elected probability of all the other wireless sensing net nodes, and compare with the elected probability of oneself;

If the elected probability of this wireless sensing net node is greater than the elected probability of all the other wireless sensing net nodes; Then this wireless sensing net node is elected to cluster head node, and all the other wireless sensing net nodes become ordinary node automatically.

The select probability of described cluster head is directly proportional to the dump energy of wireless sensing net node, and with the relative mobility of wireless sensing net node, and the offset distance of the wireless sensing net node relative bunch of heart is inversely proportional to;

The Probability p that wireless sensing net node is elected to cluster head node can be expressed as:

$p\∝e\·\frac{1}{m}\·\frac{1}{d}$

In formula, p represents that wireless sensing net node is elected to the probability of cluster head node; E represents energy factors; M represents relative movement sex factor; D represents the offset distance of the relative bunch of heart.

The computing formula of described energy factors e is:

Suppose that the primary power value of all wireless sensing net nodes is identical, be designated as E _-init, current remaining is designated as E _-current, energy factors e can be expressed as:

$e=\frac{E_{-current}}{E_{-init}}$

The computing formula of relative movement sex factor m is:

Across the sea, and the exact position of wireless sensing net node can be acquired wireless sensing net node random distribution, V={k ₁, k ₂, k ₃k _nto represent bunch in n node, and pass through information broadcasting, the positional information of neighbor node can by bunch in other nodes obtain, if t ₀the position of moment each wireless sensing net node is p (x _i, y _i, t ₀) (i=1,2,3 ... n), t ₀the position of+Δ moment each wireless sensing net node is p (x _i, y _i, t ₀+ Δ) (i=1,2,3 ... n), then wireless sensing net node j (j ∈ V) can be expressed as relative to the mobility of other wireless sensing net nodes:

$m=\frac{1}{n-1}\underset{i\∈V,i\≠j}{\Σ}|p(x_i,y_i,t_0+\mathrm{\Δ})-p(x_j,y_j,t_0+\mathrm{\Δ})|-|p(x_i,y_i,t_0)-p(x_j,y_j,t_0)|$

The computing formula of the offset distance d of the relative bunch of heart is:

If t ₀the position of moment each wireless sensing net node is P (x _i, y _i, t ₀) (i=1,2,3 ... n), then bunch in bunch heart G of all wireless sensing net nodes be:

$G(x,y,t_0)=\frac{1}{n}\underset{i\∈V}{\Σ}p(x_i,y_i,t_0)$

The offset distance d of each wireless sensing net node relative bunch of heart is:

d＝|p(x _i,y _i,t ₀)-G(x,y,t ₀)|。

Described robust method for routing also comprises step S5:

S5, a prefixed time interval is set, when described prefixed time interval arrives, re-starts cluster head election.

Presetting link stability assessment algorithm in described step S4 is comentropy rule.

Described comentropy rule comprises the step that data forwarding backbone links carries out stability measurement:

If S={l ₁, l ₂, l ₃... l _nfor being communicated with the set of the backbone links collection of certain cluster head node and aggregation node, D (l _i) representing that the neighbor node in certain link subset is gathered (m, n), N (m) represents the neighbor node collection of node m, v (m, t) for any wireless sensing net node m is in the speed of t, p (x, y, m, t) for any wireless sensing net node m is in the position of t, the then relative velocity v (m, n, t) of arbitrary neighborhood wireless sensing net node and relative displacement p (x, y, m, n, t) can be expressed as:

v(m,n,t)＝v(m,t)-v(n,t)

p(x,y,m,n,t)＝p(x,y,m,t)-p(x,y,n,t)

Structural feature vector;

a _m,n(Δ)＝|p(x,y,m,n,t+Δ)-p(x,y,m,n,t)|+Δ·|v(m,n,t+Δ)-v(m,n,t)|

Definition entropy is the mean change amount in the k Δ moment between neighbor node, that is:

H _(m,n)＝-P _m,n(t,Δ)·logP _m,n(t,Δ)

Wherein,

$P_{m,n}(t,\mathrm{\Δ})=\frac{a_{m,n}}{A_{m,n}}$

A _m,nfor node is to the average of (m, the n) characteristic vector in k delta time;

$A_{m,n}=\underset{i=1}{\overset{k}{\Σ}}\underset{t=t_0+i\mathrm{\Δ}}{\Σ}|p(x,y,m,n,t+\mathrm{\Δ})-p(x,y,m,n,t)|+\mathrm{\Δ}\·|v(m,n,t+\mathrm{\Δ})-v(m,n,t)|$

According to the definition of entropy, the entropy of whole piece link can be expressed as:

$H_l=\frac{\underset{(m,n)\∈l}{\Σ}{H}_{(m,n)}}{C\left(D\right(l\left)\right)+1}$

Wherein, C (D (l)) represents the number that link l interior joint is right, then C (D (l))+1 represents the number of link interior joint.

A kind of maritime search and rescue wireless sensing network system of the present invention and robust method for routing thereof compared with prior art have the following advantages: calculate threshold value by considering of energy distance etc., comparison node threshold value selects cluster head node, foundation is applicable to marine stable routing criterion, and the stability according to link selects routing forwarding data; The route of robust environment can be set up according to the environmental change of wireless sense network, effectively utilize sub-clustering and comentropy feature separately, the network that dynamic is higher can be adapted to, improve data transmission quality and efficiency; Based on the cluster algorithm in geographical position network to be divided and the stability of comentropy rule to all links is weighed by using, high-octane validity can be put forward, can ensure again to select metastable route in data transmission procedure, improve router efficiency.

Accompanying drawing explanation

Fig. 1 is the configuration diagram of a kind of maritime search and rescue wireless sensing network system of the present invention;

Fig. 2 A is that under dynamic environment, t communication link selects schematic diagram;

Fig. 2 B is that under dynamic environment, t+ Δ moment communication link selects schematic diagram;

Fig. 3 be the present invention compared with existing routing protocol, the schematic diagram of route success rate under different node motion speed;

Fig. 4 be the present invention compared with existing routing protocol, the schematic diagram of transmission delay under different node motion speed;

Fig. 5 be the present invention compared with existing routing protocol, the schematic diagram in different node number lower network life-span.

Embodiment

Below in conjunction with accompanying drawing, by describing a preferably specific embodiment in detail, the present invention is further elaborated.

As shown in Figure 1, a kind of maritime search and rescue wireless sensing network system, comprises: several wireless sensing net nodes 100, several aggregation nodes 200, several search and rescue terminals 300 and base station or ground control centre 400; Several described wireless sensing net node 100 random distribution, and build wireless sense network by the form of self-organizing at sea, and wireless sensing net node 100 described in each is for gathering search and rescue information data; Described aggregation node 100 carries out information interaction with wireless sensing net node 200 by communication, the search and rescue information data transmission that wireless sensing net node 100 collects by described aggregation node 200 is to searching and rescuing terminal 300, described search and rescue terminal 300 is connected to Internet by satellite 500, and base station or ground control centre 400 carry out subsequent treatment by Internet to search and rescue information data.

Particularly, search and rescue terminal, be arranged at boats and ships or search and rescue on helicopter, being established a communications link by external satellite and the Internet, aggregation node, is arranged at lifeboat raft etc., and this aggregation node is connected with the communication of search and rescue terminal wireless, wireless sensing net node is arranged at life vest or goods etc., and this wireless sensing net node real-time detection aggregation node is also connected with aggregation node wireless telecommunications, life vest or goods are equipped with wireless sensing net node with ship, when wireless sense network is disposed, wireless sensing net node primary power is identical, after overboard, wireless sensing net node is met water and is opened, self-organizing forms a multihop network, due to goods or persons falling in water due to marine stormy waves etc. impact entrained by wireless sensing net node may be relatively unstable, relatively stable is lash ship, search and rescue boats and ships and search and rescue helicopter etc., thus in order to ensure that searching and rescuing target is arrived by the network coverage as far as possible, to other wireless sensing net nodes of manually shedding search and rescue side be added and front a kind of wireless sensing net node comes together to form wireless sense network.After wireless sense network is formed, wireless sensing net node collects the information of self goods or life entity, as vital sign, and geographical position etc., then by its information transmission to aggregation node, effective information is transferred to search and rescue terminal by aggregation node again.

In conjunction with above-mentioned maritime search and rescue wireless sensing network system, the invention also discloses a kind of robust method for routing of maritime search and rescue radio sensing network, the method is based on the cluster routing method of comentropy, wireless sensing net node in wireless sense network is carried out sub-clustering based on geographical position, the stability of comentropy rule to link is adopted to weigh, optimization data repeating process, this robust method for routing comprises following steps:

S1, sub-clustering stage, adopt the cluster algorithm based on geographical position that several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out sub-clustering according to virtual grid, the wireless sensing net node being positioned at same virtual grid is same bunch, and any wireless sensing net node met in adjacent virtual grid can communicate;

S2, cluster head are elected, and several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out initialization, calculates the probability that each wireless sensing net node is elected to cluster head, and select cluster head node at random in the mode that wheel turns;

S3, Route Selection, all cluster head node in maritime search and rescue wireless sensing network system build the backbone links collection of data retransmission, cluster head node to bunch in the search and rescue information data that collects of all the other nodes carry out integration process, and forward the search and rescue information data that all the other cluster head node send;

S4, transfer of data, adopt default link stability assessment algorithm to carry out stability measurement to all data retransmission backbone links that the data retransmission backbone links that cluster head node builds is concentrated, select optimal data to forward backbone links and will integrate the search and rescue information data transmission after processing to aggregation node.

In the present embodiment, presetting link stability assessment algorithm in described step S4 is comentropy rule.

Election of cluster head

Example of the present invention is when wireless sense network is disposed, wireless sensing net node primary power is identical (this wireless sensing net node can be the wireless sensing net node that goods or persons falling in water carry, and also can be shed afloat wireless sensing net node).Based on GPS location or relevant node locating algorithm, wireless sensing net node can obtain self geographical position, namely GAF sub-clustering usage carries out stress and strain model according to geographical position to wireless sensing net node, and the node met in adjacent mesh can realize communication, then must meet between the length of side a of virtual grid and the communication radius R of node:

$a^2+{\left(2a\right)}^2\≤R^2\⇒a\≤\frac{R}{\sqrt{5}}$

After virtual grid divides, wireless sensing net node in same virtual grid belongs to same bunch, carry out the election of cluster head, in the process of cluster head election, consider the dump energy of node, node bunch in position and relative mobility between node and other nodes, computing node is elected to the probability of cluster head, wherein:

The computing formula of energy factors e is:

Suppose that the primary power value of all wireless sensing net nodes is identical, be designated as E _-init, current remaining is designated as E _-current, energy factors e can be expressed as:

$e=\frac{E_{-current}}{E_{-init}}$

The computing formula of relative movement sex factor m is:

Across the sea, and the exact position of wireless sensing net node can be acquired wireless sensing net node random distribution, V={k ₁, k ₂, k ₃k _nto represent bunch in n node, and pass through information broadcasting, the positional information of neighbor node can by bunch in other nodes obtain, if t ₀the position of moment each wireless sensing net node is p (x _i, y _i, t ₀) (i=1,2,3 ... n), t ₀the position of+Δ moment each wireless sensing net node is p (x _i, y _i, t ₀+ Δ) (i=1,2,3 ... n), then wireless sensing net node j (j ∈ V) can be expressed as relative to the mobility of other wireless sensing net nodes:

$m=\frac{1}{n-1}\underset{i\∈V,i\≠j}{\Σ}|p(x_i,y_i,t_0+\mathrm{\Δ})-p(x_j,y_j,t_0+\mathrm{\Δ})|-|p(x_i,y_i,t_0)-p(x_j,y_j,t_0)|$

The computing formula of the offset distance d of the relative bunch of heart is:

If t ₀the position of moment each wireless sensing net node is P (x _i, y _i, t ₀) (i=1,2,3 ... n), then bunch in bunch heart G of all wireless sensing net nodes be:

$G(x,y,t_0)=\frac{1}{n}\underset{i\∈V}{\Σ}p(x_i,y_i,t_0)$

The offset distance d of each wireless sensing net node relative bunch of heart is:

d＝|p(x _i,y _i,t ₀)-G(x,y,t ₀)|。

Consider, the select probability of described cluster head is directly proportional to the dump energy of wireless sensing net node, and with the relative mobility of wireless sensing net node, and the offset distance of the wireless sensing net node relative bunch of heart is inversely proportional to;

The Probability p that wireless sensing net node is elected to cluster head node can be expressed as:

$p\∝e\·\frac{1}{m}\·\frac{1}{d}$

In formula, p represents that wireless sensing net node is elected to the probability of cluster head node; E represents energy factors; M represents relative movement sex factor; D represents the offset distance of the relative bunch of heart.

Each wireless sensing net node in bunch calculates oneself elected possibility according to the select probability of cluster head, and bunch in broadcast;

Receive the elected probability of all the other wireless sensing net nodes, and compare with the elected probability of oneself;

If the elected probability of this wireless sensing net node is greater than the elected probability of all the other wireless sensing net nodes; Then this wireless sensing net node is elected to cluster head node, and all the other wireless sensing net nodes become ordinary node automatically.

In the present embodiment, preferably, a step S5 is also comprised;

S5, a prefixed time interval is set, when described prefixed time interval arrives, re-starts cluster head election.

Energy balane adopts with drag: node a sends the data of k byte to another node b outside distance d, and energy consumption calculation mode is as follows:

$E_{T_r(k,d)}=E_{elec\left(k\right)}+E_{amp(k,d)}=\left\{\begin{array}{cc}{\mathrm{kE}}_{elec}+{\mathrm{k\ϵ}}_{fs}{d}^2& d\≤d_0\\ {\mathrm{kE}}_{elce}+{\mathrm{k\ϵ}}_{mp}{d}^4& d>d_0\end{array}\right.---\left(6\right)$

Wherein, E _{elec (k)}it is the energy that transtation mission circuit transmission k byte data consumes; E _{amp (k, d)}it is the energy that emission amplifier consumes; E _elecbe the energy that transtation mission circuit sends data consumes, depend on the factors such as digital code, filtering module and signal diffusion; ε _fsit is the specific energy consumption value of free space model emission amplifier; ε _mpit is the specific energy consumption value of multipath fading model emission amplifier; ε _fsd ²and ε _mpd ⁴parameter value is determined by the value of the data bit error rate in the distance and communication process of receiver; d ₀it is the distance value of a setting.

And node b is when receiving the message from node a, the energy consumption that its radio receiver produces is:

E _Rx(k)＝kE _elec(7)

The false code of algorithm 1 is as follows:

Selecting paths and data transfer phae

Described comentropy rule comprises the step that data forwarding backbone links carries out stability measurement:

If S={l ₁, l ₂, l ₃... l _nfor being communicated with the set of the backbone links collection of certain cluster head node and aggregation node, D (l _i) representing that the neighbor node in certain link subset is gathered (m, n), N (m) represents the neighbor node collection of node m, v (m, t) for any wireless sensing net node m is in the speed of t, p (x, y, m, t) for any wireless sensing net node m is in the position of t, the then relative velocity v (m, n, t) of arbitrary neighborhood wireless sensing net node and relative displacement p (x, y, m, n, t) can be expressed as:

v(m,n,t)＝v(m,t)-v(n,t)

p(x,y,m,n,t)＝p(x,y,m,t)-p(x,y,n,t)

Structural feature vector;

a _m,n(Δ)＝|p(x,y,m,n,t+Δ)-p(x,y,m,n,t)|+Δ·|v(m,n,t+Δ)-v(m,n,t)|

Definition entropy is the mean change amount in the k Δ moment between neighbor node, that is:

H _(m,n)＝-P _m,n(t,Δ)·logP _m,n(t,Δ)

Wherein,

$P_{m,n}(t,\mathrm{\Δ})=\frac{a_{m,n}}{A_{m,n}}$

A _m,nfor node is to the average of (m, the n) characteristic vector in k delta time;

$A_{m,n}=\underset{i=1}{\overset{k}{\Σ}}\underset{t=t_0+i\mathrm{\Δ}}{\Σ}|p(x,y,m,n,t+\mathrm{\Δ})-p(x,y,m,n,t)|+\mathrm{\Δ}\·|v(m,n,t+\mathrm{\Δ})-v(m,n,t)|$

According to the definition of entropy, when system event adds up to N, H≤logN, and if only if P ₁=P ₂=...=P _nduring=1/N, equal sign is set up.We can obtain thus, and entropy is larger, and the link between neighbor node is more stable.The entropy of whole piece link can be expressed as:

$H_l=\frac{\underset{(m,n)\∈l}{\Σ}{H}_{(m,n)}}{C\left(D\right(l\left)\right)+1}$

Wherein, C (D (l)) represents the number that link l interior joint is right, then C (D (l))+1 represents the number of link interior joint.

The present invention is the robust retransmission method being suitable for maritime environment.The data collected are sent to cluster head node by all nodes in bunch, cluster head node to collect bunch in member node information after formed a packets of information (bundle), then through the data retransmission backbone links collection that built by cluster head node by data retransmission to aggregation node.Consider the mobility of node, go out there will be node motion the situation that current cluster enters other bunches, this re-starts the renewal of node in just needing bunch, re-start the election of cluster head, therefore arrange a TCP timer here, re-starts cluster head election when envoy presses by it.

The false code of algorithm 2 source node is as follows:

The process efficiently utilizes the advantage of the cluster algorithm based on geographical position, geographical location information according to node carries out Region dividing to node, facilitate management and the control of node, avoid sending the obstruction that a large amount of data cause network in a network simultaneously, integration process is carried out to data, avoid the redundancy of data, save the energy loss that data send, utilize the backbone links collection built by cluster head node to carry out the transmission of data simultaneously, and adopt the stability of comentropy rule to link to weigh, more stable link is selected to carry out the forwarding of data, avoid repeating to create route, the forwarding data of network node maximal efficiency can be made.Therefore this method has better adaptability to maritime environment.

Robust method for routing below by the problem model set up the present invention and invention carries out sunykatuib analysis, introduces execution mode and the advantage in actual applications thereof of example of the present invention further.This sunykatuib analysis can adopt emulation platform to carry out.

This method utilizes NS2 platform to carry out emulation platform to carry out Computer Simulation.Optimum configurations is as follows: in the square shaped sensor region of 1000m*1000m, and random dispersion 200 nodes.Emulation adopts this research Routing Protocol (showing in the drawings for EGRA), Flooding, DSR and AODV.

Arrange as table is arranged the parameter of network distribution region and node, as shown in the table.

Three kinds of agreements are contrasted from following three aspects:

(1) route success rate.

(2) average time delay end to end.

(3) network life.

As shown in Figure 3, the simulation result of four kinds of algorithm route success rates is given.Distribute the constantly motion of afloat wireless sense network due to node, causing internodal communication path off and on, needing the connectedness ensureing link by repeatedly rebuilding route, route success rate characterize institute's road construction by stability.As seen from the figure, compared with other algorithms, the route success rate of algorithm is higher herein, reason is herein in establishing route process, using stable for path as a significant consideration, by choosing the path of a most stable link as transfer of data, route success rate is the highest, and other three kinds of algorithms do not consider the stability of link, DSR is only second to AODV, and Flooding route success rate is minimum.

Fig. 4 is the simulation result of the average end-to-end path time delay of each routing algorithm.Path delay indicates the message transmission rate in link end to end, and link is more stable, is more conducive to transfer of data.As seen from the figure, proposed algorithm data transmission delay is minimum, reason is in the process of establishing route, select node relative mobility less, the link that retention time is long, decrease the process repeating to create routed path, and DSR and AODV algorithm is all Stochastic choice link, due to the mobility of nodes, the connectedness of link can not be ensured, can only route be rebuild when the link is broken, thus increase the time delay of transfer of data.Flooding carries out the inundation of data, has increased the weight of the obstruction of link and the redundancy of data, causes time delay end to end the highest.

Fig. 5 gives the simulation result of network life.A maximum limiting factor of wireless sensing net node is exactly energy, equalizing network energy consumption becomes the significant consideration of this algorithm, wherein, Flooding algorithm does not adopt any optimized algorithm, redundant data is not processed in the whole process of carrying out transfer of data, increase the weight of the burden of network service, energy ezpenditure is more, network life is the shortest, with AODV, DSR compares, algorithm in this paper adopts stabilizing path to transmit, decrease the number of times of rerouting, consider energy ezpenditure simultaneously, decrease the universe network energy consumption in network service process, effectively extend the life-span of network.

In sum, the route that the present invention can set up robust environment according to the environmental change of wireless sense network is estimated; Effective utilization to the measurement of link stability based on the sub-clustering in geographical position and comentropy, makes routing algorithm can be applicable to marine mobile environment, improves the quality of transfer of data.

Although content of the present invention has done detailed introduction by above preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple amendment of the present invention and substitute will be all apparent.Therefore, protection scope of the present invention should be limited to the appended claims.

Claims (10)

1. a maritime search and rescue wireless sensing network system, is characterized in that, comprises:

Several wireless sensing net nodes, several aggregation nodes, several search and rescue terminals and base station or ground control centre;

Several described wireless sensing net node random distribution, and build wireless sense network by the form of self-organizing at sea, and wireless sensing net node described in each is for gathering search and rescue information data;

Described aggregation node and wireless sensing net node carry out information interaction by communication, the search and rescue information data transmission that wireless sensing net node collects by described aggregation node is to searching and rescuing terminal, described search and rescue terminal is connected to Internet by satellite, and base station or ground control centre carry out subsequent treatment by Internet to search and rescue information data.

2. maritime search and rescue wireless sensing network system as claimed in claim 1, is characterized in that, several described wireless sensing net nodes comprise the wireless sensing net node being arranged on wireless sensing net node on life vest or goods and search and rescue side and manually shedding; Several described aggregation nodes are arranged on lifeboat raft; Described search and rescue terminal is arranged on boats and ships or searches and rescues on aircraft; Wherein the primary power of several wireless sensing net nodes is identical.

3. maritime search and rescue wireless sensing network system as claimed in claim 1, is characterized in that, described search and rescue information data comprises goods information and/or vital sign information and/or geographical position.

4. a robust method for routing for maritime search and rescue radio sensing network, is applied to maritime search and rescue wireless sensing network system, it is characterized in that, comprise following steps:

S1, sub-clustering stage, adopt the cluster algorithm based on geographical position that several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out sub-clustering according to virtual grid, the wireless sensing net node being positioned at same virtual grid is same bunch, and any wireless sensing net node met in adjacent virtual grid can communicate;

S2, cluster head are elected, and several wireless sensing net nodes in maritime search and rescue wireless sensing network system are carried out initialization, calculates the probability that each wireless sensing net node is elected to cluster head, and select cluster head node at random in the mode that wheel turns;

S3, Route Selection, all cluster head node in maritime search and rescue wireless sensing network system build the backbone links collection of data retransmission, cluster head node to bunch in the search and rescue information data that collects of all the other nodes carry out integration process, and forward the search and rescue information data that all the other cluster head node send;

S4, transfer of data, adopt default link stability assessment algorithm to carry out stability measurement to all data retransmission backbone links that the data retransmission backbone links that cluster head node builds is concentrated, select optimal data to forward backbone links and will integrate the search and rescue information data transmission after processing to aggregation node.

5. robust method for routing as claimed in claim 4, is characterized in that, specifically comprise in described step S2:

Each wireless sensing net node in bunch calculates oneself elected possibility according to the select probability of cluster head, and bunch in broadcast;

Receive the elected probability of all the other wireless sensing net nodes, and compare with the elected probability of oneself;

If the elected probability of this wireless sensing net node is greater than the elected probability of all the other wireless sensing net nodes; Then this wireless sensing net node is elected to cluster head node, and all the other wireless sensing net nodes become ordinary node automatically.

6. robust method for routing as claimed in claim 5, it is characterized in that, the select probability of described cluster head is directly proportional to the dump energy of wireless sensing net node, and with the relative mobility of wireless sensing net node, and the offset distance of the wireless sensing net node relative bunch of heart is inversely proportional to;

The Probability p that wireless sensing net node is elected to cluster head node can be expressed as:

$p\∝e\·\frac{1}{m}\·\frac{1}{d}$

In formula, p represents that wireless sensing net node is elected to the probability of cluster head node; E represents energy factors; M represents relative movement sex factor; D represents the offset distance of the relative bunch of heart.

7. robust method for routing as claimed in claim 6, it is characterized in that, the computing formula of described energy factors e is:

Suppose that the primary power value of all wireless sensing net nodes is identical, be designated as E _-init, current remaining is designated as E _-current, energy factors e can be expressed as:

$e=\frac{E_{-current}}{E_{-init}}$

The computing formula of relative movement sex factor m is:

Across the sea, and the exact position of wireless sensing net node can be acquired wireless sensing net node random distribution, V={k ₁, k ₂, k ₃k _nto represent bunch in n node, and pass through information broadcasting, the positional information of neighbor node can by bunch in other nodes obtain, if t ₀the position of moment each wireless sensing net node is p (x _i, y _i, t ₀) (i=1,2,3 ... n), t ₀the position of+Δ moment each wireless sensing net node is p (x _i, y _i, t ₀+ Δ) (i=1,2,3 ... n), then wireless sensing net node j (j ∈ V) can be expressed as relative to the mobility of other wireless sensing net nodes:

$m=\frac{1}{n-1}\underset{i\∈V,i\≠j}{\Σ}|p(x_i,y_i,t_0+\mathrm{\Δ})-p(x_j,y_j,t_0+\mathrm{\Δ})|-|p(x_i,y_i,t_0)-p(x_j,y_j,t_0)|$

The computing formula of the offset distance d of the relative bunch of heart is:

If t ₀the position of moment each wireless sensing net node is P (x _i, y _i, t ₀) (i=1,2,3 ... n), then bunch in bunch heart G of all wireless sensing net nodes be:

$G(x,y,t_0)=\frac{1}{n}\underset{i\∈V}{\Σ}p(x_i,y_i,t_0)$

The offset distance d of each wireless sensing net node relative bunch of heart is:

d＝|p(x _i，y _i，t ₀)-G(x，y，t ₀)|。

8. robust method for routing as claimed in claim 4, is characterized in that, comprise step S5 further:

S5, a prefixed time interval is set, when described prefixed time interval arrives, re-starts cluster head election.

9. robust method for routing as claimed in claim 4, is characterized in that, presetting link stability assessment algorithm in described step S4 is comentropy rule.

10. robust method for routing as claimed in claim 9, is characterized in that, described comentropy rule comprises the step that data forwarding backbone links carries out stability measurement:

If S={l ₁, l ₂, l ₃l _nfor being communicated with the set of the backbone links collection of certain cluster head node and aggregation node, D (l _i) representing that the neighbor node in certain link subset is gathered (m, n), N (m) represents the neighbor node collection of node m, v (m, t) for any wireless sensing net node m is in the speed of t, p (x, y, m, t) for any wireless sensing net node m is in the position of t, the then relative velocity v (m, n, t) of arbitrary neighborhood wireless sensing net node and relative displacement p (x, y, m, n, t) can be expressed as:

v(m，n，t)＝v(m，t)-v(n，t)

p(p，y，m，n，t)＝p(x，y，m，t)-p(x，y，n，t)

Structural feature vector;

a _m，n(Δ)＝|p(x，y，m，n，t+Δ)-p(x，y，m，n，t)|+Δ·|v(m，n，t+Δ)-v(m，n，t)|

Definition entropy is the mean change amount in the k Δ moment between neighbor node, that is:

H _(m，n)＝-P _m，n(t，Δ).logP _m，n(t，Δ)

Wherein,

$P_{m,n}(t,\mathrm{\Δ})=\frac{a_{m,n}}{A_{m,n}}$

A _{m, n}for node is to the average of (m, the n) characteristic vector in k delta time;

$A_{m,n}=\underset{i=1}{\overset{k}{\Σ}}\underset{t=t_0+i\mathrm{\Δ}}{\Σ}|p(x,y,m,n,t+\mathrm{\Δ})-p(x,y,m,n,t)|+\mathrm{\Δ}\·|v(m,n,t+\mathrm{\Δ})-v(m,n,t)|$

According to the definition of entropy, the entropy of whole piece link can be expressed as:

$H_l=\frac{\underset{(m,n)\∈l}{\Σ}{H}_{(m,n)}}{C\left(D\right(l))+1}$

Wherein, the number l that C (D (l)) expression link l interior joint is right then C (D (l))+1 represents the number of link interior joint.